Finding the Flow Again and Again

How to feel more engaged at work

Do you find it difficult to detach yourself from work at the end of the day, especially if you have been working from home more this year? Are you able to really switch off or do you find your thoughts steering back towards your to-do list?

While it may feel counterintuitive to stop thinking about work when you know you will have a complex day ahead, it is important to detach yourself mentally from work during non-work time. When you can put your mind off work during your non-work time, research shows, your brain gets some time to reset and this can help preserve your engagement and performance at work the next day.

Another important factor that helps to increase work engagement throughout the day, as research by Sabine Sonnentag and Jana Kühnel has shown, is taking time to reattach to your work before starting your day. You can reattach by running the upcoming day through your head while you are having breakfast at home, during your commute or even during the first few minutes at work. Clarifying your goals for the day makes it easier to transition to your work tasks, as your task attention will already be increased before starting to work. You will find it easier to get absorbed back in your work, which can be tough, especially on Monday mornings.

Another great way to reattach is making a schedule for the day. When you are making your schedule, start with the tasks you are not looking forward to and plan more exciting tasks towards the end of the day, as Sonnentag and Kühnel also found that work engagement is naturally higher in the morning than in the afternoon.

Early Trauma Influences Metabolism Across Generations

Summary: Early childhood trauma has an impact on glucose metabolism and blood composition, which are passed on to the next generation.

Source: University of Zurich

People who live through traumatic experiences in childhood often suffer long-lasting consequences that affect their mental and physical health. But moreover, their children and grand-children can also be impacted as well. In this particular form of inheritance, sperm and egg cells pass on information to offspring not through their DNA sequence like classical genetic heredity, but rather via biological factors involving the epigenome that regulates genome activity. However, the big question is how the signals triggered by traumatic events become embedded in germ cells.

“Our hypothesis was that circulating factors in blood play a role,” says Isabelle Mansuy, professor of neuroepigenetics at the University of Zurich’s Brain Research Institute and the ETH Zurich’s Institute for Neuroscience. Mansuy and her team demonstrated that childhood trauma does have a lifelong influence on blood composition and that these changes are also passed to the next generation. “These findings are extremely important for medicine, as this is the first time that a connection between early trauma and metabolic disorders in descendants is characterized,” explains Mansuy.

Traumatic stress leads to metabolic changes across generations

In her study, Mansuy used a mouse model for early trauma that had been developed in her lab. The model is used to study how the effects of trauma in early postnatal life on male mice are transmitted to their offspring. To determine whether these early experiences have an impact on blood composition, the researchers conducted multiple analyses and found large and significant differences between blood from adult traumatized animals and blood from normal, non-traumatized control group.

Changes in lipid metabolism were particularly striking, with certain polyunsaturated fatty acids metabolites appearing in higher concentrations in the blood of traumatized male mice. These same changes were also observed in their offspring. Even more strikingly, when the serum of traumatized males was chronically injected into non-traumatized males, their offspring also developed metabolic symptoms of trauma – providing a direct link between circulating factors and germ cells, thus confirming the hypothesis that blood delivers stress signals to the gametes.

Comparison with traumatized children

The researchers then investigated whether similar effects are present in humans. For this, they assembled a cohort of 25 children from an SOS Children’s Village in Pakistan who have lost their father and were separated from their mother, and analyzed their blood and saliva. When compared with children from normal families, the orphans showed higher level of several lipid metabolites – just like the traumatized mice.

“These children’s traumatic experiences are comparable to those in our mouse model, and their metabolism show similar changes in blood,” explains Mansuy. “This demonstrates the importance of animal research for providing us with fundamental insights into human health.” Up to one fourth of children across the world experience violence, abuse and neglect, that can lead to chronic diseases later in their life, highlighting the importance of Mansuy’s research.

Receptor interferes with gametes

Further experiments led the team to discover a molecular mechanism by which lipid metabolites can transmit signals to animals’ germ cells. PPAR, a receptor at the surface of cells, plays a key role in this process; it is activated by fatty acids and regulates gene expression and DNA structure in numerous tissues. The researchers discovered that this receptor is upregulated in the sperm of traumatized males.

Neurologic and neuroimaging findings in patients with COVID-19

Stéphane Kremer, François Lersy, Mathieu Anheim, Hamid Merdji, Maleka Schenck, Hélène Oesterlé, Federico Bolognini, Julien Messie, Antoine Khalil, Augustin Gaudemer, Sophie Carré, Manel Alleg, Claire Lecocq, Emmanuelle Schmitt, René Anxionnat,  View ORCID ProfileFrançois Zhu, Lavinia Jager, Patrick Nesser, Yannick Talla Mba, Ghazi Hmeydia,  View ORCID ProfileJoseph Benzakoun, Catherine Oppenheim, Jean-Christophe Ferré, Adel Maamar, Béatrice Carsin-Nicol,  View ORCID ProfilePierre-Olivier Comby, Frédéric Ricolfi, Pierre Thouant,  View ORCID ProfileClaire Boutet, Xavier Fabre,  View ORCID ProfileGéraud Forestier, Isaure de Beaurepaire, Grégoire Bornet, Hubert Desal,  View ORCID ProfileGrégoire Boulouis, Jérome Berge, Apolline Kazémi, Nadya Pyatigorskaya, Augustin Lecler, Suzana Saleme, Myriam Edjlali-Goujon, Basile Kerleroux, Jean-Marc Constans, Pierre-Emmanuel Zorn, Muriel Mathieu,  View ORCID ProfileSeyyid Baloglu,  View ORCID ProfileFrançois-Daniel Ardellier, Thibault Willaume,  View ORCID ProfileJean-Christophe Brisset, Sophie Caillard, Olivier Collange, Paul Michel Mertes, Francis Schneider, Samira Fafi-Kremer,  View ORCID ProfileMickael Ohana, Ferhat Meziani, Nicolas Meyer, Julie Helms,  View ORCID ProfileFrançois CottonFirst published July 17, 2020, DOI:

Objective To describe neuroimaging findings and to report the epidemiologic and clinical characteristics of patients with coronavirus disease 2019 (COVID-19) with neurologic manifestations.

Methods In this retrospective multicenter study (11 hospitals), we included 64 patients with confirmed COVID-19 with neurologic manifestations who underwent a brain MRI.

Results The cohort included 43 men (67%) and 21 women (33%); their median age was 66 (range 20–92) years. Thirty-six (56%) brain MRIs were considered abnormal, possibly related to severe acute respiratory syndrome coronavirus. Ischemic strokes (27%), leptomeningeal enhancement (17%), and encephalitis (13%) were the most frequent neuroimaging findings. Confusion (53%) was the most common neurologic manifestation, followed by impaired consciousness (39%), presence of clinical signs of corticospinal tract involvement (31%), agitation (31%), and headache (16%). The profile of patients experiencing ischemic stroke was different from that of other patients with abnormal brain imaging: the former less frequently had acute respiratory distress syndrome (p = 0.006) and more frequently had corticospinal tract signs (p = 0.02). Patients with encephalitis were younger (p = 0.007), whereas agitation was more frequent for patients with leptomeningeal enhancement (p = 0.009).

Conclusions Patients with COVID-19 may develop a wide range of neurologic symptoms, which can be associated with severe and fatal complications such as ischemic stroke or encephalitis. In terms of meningoencephalitis involvement, even if a direct effect of the virus cannot be excluded, the pathophysiology seems to involve an immune or inflammatory process given the presence of signs of inflammation in both CSF and neuroimaging but the lack of virus in CSF.

Methods In this retrospective multicenter study (11 hospitals), we included 64 patients with confirmed COVID-19 with neurologic manifestations who underwent a brain MRI.

Results The cohort included 43 men (67%) and 21 women (33%); their median age was 66 (range 20–92) years. Thirty-six (56%) brain MRIs were considered abnormal, possibly related to severe acute respiratory syndrome coronavirus. Ischemic strokes (27%), leptomeningeal enhancement (17%), and encephalitis (13%) were the most frequent neuroimaging findings. Confusion (53%) was the most common neurologic manifestation, followed by impaired consciousness (39%), presence of clinical signs of corticospinal tract involvement (31%), agitation (31%), and headache (16%). The profile of patients experiencing ischemic stroke was different from that of other patients with abnormal brain imaging: the former less frequently had acute respiratory distress syndrome (p = 0.006) and more frequently had corticospinal tract signs (p = 0.02). Patients with encephalitis were younger (p = 0.007), whereas agitation was more frequent for patients with leptomeningeal enhancement (p = 0.009).

Conclusions Patients with COVID-19 may develop a wide range of neurologic symptoms, which can be associated with severe and fatal complications such as ischemic stroke or encephalitis. In terms of meningoencephalitis involvement, even if a direct effect of the virus cannot be excluded, the pathophysiology seems to involve an immune or inflammatory process given the presence of signs of inflammation in both CSF and neuroimaging but the lack of virus in CSF.

What Happens in Your Brain When You Make Memories?

Maybe it’s a hazy snapshot of your first time riding a bicycle. Or the ability to recite the Pythagorean theorem. It could be as simple as that phone number you scrawled on a napkin before it landed in the trash.

Whatever shape they take, our memories help define who we are — and what it means to be human. While scholars have been musing on memory since the time of Socrates, new tech has helped today’s scientists learn much more about the neural and biological machinery behind our recollections. These breakthroughs have led to the discovery that our memories reside in specific clusters of brain cells. Some scientists are exploring how people store and retrieve memories as they move through a virtual reality environment. Others are studying how emotions like fear are encoded in the brain, as well as the circuitry that controls what we’re afraid of.

This research isn’t rooted in the abstract, either. The projects are aimed at real-world applications, including possible treatments for conditions such as Alzheimer’s disease and post-traumatic stress disorder.

And while much of memory science is still a blur, the matter of how, exactly, our brains form memories is coming into sharper focus.

Brain Diagram - Science Source

(Credit: Evan Oto/Science Source)

The Long and Short of It

The notion of human memory doesn’t refer to any one thing. The term is an umbrella for an array of recollections, from the names of colors to half-remembered song lyrics to your first breakup. So, what are these different types of memory?

Over a century ago, scientists partitioned memory into short-term and long-term categories. Short-term memory, sometimes called working memory, refers to our ability to retain information or events from the recent past — but only for as long as about 20 seconds ago, sometimes even less. In other words, it’s the stuff that you’re actively holding in your head while performing other tasks — for example, remembering a phone number as you scroll around to plug it into your contacts list.

In the 1990s, scientists analyzed high-resolution brain scans and found that these fleeting memories depend on neurons firing in the prefrontal cortex, the front part of the brain responsible for higher-level thinking.

“They are temporary [memories],” says neuroscientist and author Dean Burnett. “It’s not meant to be for long-term storage, because they’re constantly changing and constantly in flux.

“If you hold something in the brain long enough, you can turn it into a long-term memory,” he adds. “That’s why, if you recite something like a phone number, you can eventually remember it quite easily. But if too much stuff keeps coming in, your short-term memory gets overloaded and the first [bits of information] will get kicked out.”

memories (2)

(Credit: Macrovector/Shutterstock; mything/Shutterstock)

By contrast, long-term memory is the treasure trove of knowledge and past events collected throughout our lives. And while short-term memories are supported by blips of neural activity, long-term memories actually forge a physical presence in the brain. When a long-term memory is formed, the connections between neurons, known as synapses, are strengthened. In some cases, entirely new synapses are created. And the more we revisit memories, activating these neural pathways, the stronger the connections become — like trampling your way through the woods to create a well-trodden path.

Long-term memories can also take several different forms. For example, implicit memories are the basis for automatic behaviors like tying your shoes or brushing your teeth. These instinctive actions take place in the unconscious part of the brain. “This is why people with amnesia can still do these things, even if they have no memory of doing them before,” says Burnett. “The training takes hold.”

Long-term remembrances that we’re actively aware of, however, are known as explicit memories. These are split between episodic and semantic memory. The latter describes specific, conceptual knowledge, like the date on which the Declaration of Independence was signed. Episodic memory describes events and experiences from your own life. Everything from your 21st birthday party to your trip to Europe falls into this category.

“Semantic memory is [knowing] that Paris is the capital of France,” says Burnett. “Episodic memory is [remembering] that time I went to France and threw up off the Eiffel Tower.”

Lighting The Way

MIT Memory Trace Mouse

MIT scientists labeled the cells (highlighted in red) where memory engrams are stored in a mouse hippocampus. (Credit: Steve Ramirez and Xu Liu)

The things we do in life leave traces behind, embedded in our memories. Much like Marcel Proust biting into his much-loved madeleines, causing once-forgotten memories from his childhood to come flooding back, memory traces can conjure vivid sensory experiences of things past. Since the days of ancient Greece, scholars have speculated that these remnants might even alter the physical makeup of the brain. But it wasn’t until the turn of the 20th century that scientific models of this process began to emerge. In 1904, a German scientist named Richard Semon suggested that these traces, which he called memory engrams, are represented as physical changes in the brain after an event or experience. “At the time, there was no technology to identify those brain cells which hold the specific engram for a specific memory,” says Susumu Tonegawa, professor of biology and neuroscience at MIT and winner of the 1987 Nobel Prize in Physiology or Medicine.

Researchers discover the mathematical system used by the brain to organize visual objects

When Plato set out to define what made a human a human, he settled on two primary characteristics: We do not have feathers, and we are bipedal (walking upright on two legs). Plato’s characterization may not encompass all of what identifies a human, but his reduction of an object to its fundamental characteristics provides an example of a technique known as principal component analysis.

Now, Caltech researchers have combined tools from machine learning and neuroscience to discover that the brain uses a mathematical system to organize visual objects according to their principal components. The work shows that the brain contains a two-dimensional map of cells representing different objects. The location of each cell in this map is determined by the principal components (or features) of its preferred objects; for example, cells that respond to round, curvy objects like faces and apples are grouped together, while cells that respond to spiky objects like helicopters or chairs form another group.

The research was conducted in the laboratory of Doris Tsao (BS ’96), professor of biology, director of the Tianqiao and Chrissy Chen Center for Systems Neuroscience and holder of its leadership chair, and Howard Hughes Medical Institute Investigator. A paper describing the study appears in the journal Nature on June 3.

“For the past 15 years, our lab has been studying a peculiar network in the primate brain’s temporal lobe that is specialized for processing faces. We called this network the ‘face patch network.’ From the very beginning, there was a question of whether understanding this face network would teach us anything about the general problem of how we recognize objects. I always dreamed it would, and now this has been vindicated in a startling way. It turns out that the face patch network has multiple siblings, which together form an orderly map of object space. So, face patches are one piece of a much bigger puzzle, and we can now begin to see how the entire puzzle is put together,” says Tsao.

The brain’s inferotemporal (IT) cortex is a critical center for the recognition of objects. Different regions or “patches” within the IT cortex encode for the recognition of different things. In 2003, Tsao and her collaborators discovered that there are six face patches; there are also patches that encode for bodies, scenes, and colors. But these well-studied islands only make up some of IT cortex, and the functions of the brain cells located in between them have not been well understood.

Why Do Our Brains Have Folds?

Most of us have long accepted that our brains look like overgrown, shriveled walnuts. But why do our brains have those telltale wrinkles?

The cortex, or the outer surface of the brain — what’s colloquially referred to as “gray matter” — expands and subsequently folds as our brains develop in the womb, said Lisa Ronan, a research fellow in the Department of Psychiatry at the University of Cambridge in England.

In essence, this expansion causes pressure to increase in that outer surface, which is then mitigated by folding, Ronan, told Live Science. [What If Humans Were Twice as Intelligent?]

The Human Brain: Blessing and Curse

Our brains are mysterious, fragile, and mischievous. That’s what makes them fascinating.


The most exciting thing about science is that it can ferry humanity into the unknown. The scientific method, as a mode of observation piloted by humans for generations, has probed outer space, the depths of the oceans, and the inner reaches of cells, molecules, and atoms—our amazing brains at the helm. Never satisfied, the three-pound, skull-encased lump of flesh strains to know more, discover more, solve more. And the universe obliges. Unimaginably vast swaths of space lie unexplored; most of the ocean floor remains a mystery; and new insights into the functioning of cells and the nature of subatomic matter emerge on an almost daily basis.

This almost unfathomable potential for discovery and innovation always rockets to the fore of my own three-pound fleshlump when it comes time to edit our annual issue on neuroscience.

Most scientists and science enthusiasts I’ve met are intellectually inflamed by the fact that there is so much out there (and in here) that we don’t know—a passion that transcends disciplines. And is there any mystery more fascinating than the functioning of the human brain itself? After all, we carry our brains around with us every day and use them to ferret out the patterns and meanings that throng around us. Neuroscientists, even more than the rest of us, use theirs to think about thinking.

Yet, after millennia of intimate interactions with our own brains and decades of formal study of the organ, “how the brain works was and still is a complete mystery,” in the words of Albert Einstein College of Medicine neuroscientist Kamran Khodakhah, this month’s profilee.

How in the name of Ramón y Cajal can cells, amassed in tangled networks and swapping ions across their membranes to propagate waves of electrical potential, result in a thought? How does this sequence of physical events form moving pictures, symphonies, emotions, and inspiration? It truly boggles . . . well, the brain.


But despite the black box around the connection between the human brain and the mind, it is clear that the flesh-and-blood organ is subject to all the ills that befall any collection of biological cells and tissues. Our brains become stuck in ruts. Our brains degenerate. Our brains deceive us.

The fragility of the human brain takes our investigations into the nuts and bolts of consciousness beyond the realm of mere curiosity. Studying brain function can help humans dodge or delay at least some of the ravages of time, environmental insult, and biological malfunction.

In this issue, two feature articles explore emerging ideas poised to reshape our concept of brain physiology. Our cover story, by Catherine Offord, relays the latest scientific findings on the impact of air pollution on neurodevelopment and cognitive function. In the second article, Ashley Yeager offers a fresh perspective on the contribution of lysosomal dysfunction to the development of Parkinson’s disease.

Reaction time deficits incurred by Cumulative Mild Head Injury (CMHI) and Post-Concussion Symptoms (PCS) between contact and non-contact sport players: A prospective study

Journal of Psychology in Africa, 2016 Vol. 26, No. 6, 555-557, © 2016 Africa Scholarship Development Enterprize 


Taylor & Francis Group 


Reaction time deficits incurred by Cumulative Mild Head Injury (CMHI) and Post-Concussion Symptoms (PCS) between contact and non-contact sport players: A prospective study 

Patricia Maite, Kathryn Nel, and Saraswathic Govender

‘Department of Psychology, Sefako Makgatho University, Garankuwa, South Africa Department of Psychology, University of Limpopo, Polokwane, South Africa 

*Corresponding author email: 

This prospective study investigated possible differential effects on reaction time and post-concussion symptoms contrasting contact and non-contact sport athletes. Participants were a purposive sample of football (soccer) players (n = 15) and volleyball players (17 = 15) from South Africa. They completed a reaction time measures pre-season and post-season. The data were analysed using the Fisher’s Exact Test and descriptive statistics. The study findings indicate a significantly higher sequential reaction time scores on the California Computerised Assessment Programme (CalCAP) for football players post-season compared to pre-season, and that some post-concussive symptoms (PCS) persisted after an initial concussion in the football-playing group or post-season. Results for ‘improved symptomology indicated that there was a small, significant difference between the football and volleyball groups post-season. 

Keywords: Cumulative Mild Head Injury (CMHI), post-concussive symptomology (PCS), football, volleyball 


Participants and setting. 

A purposive sample of male football players (n = 15) and male volleyball players (n = 15) was drawn from a population of 30 football players and 30 volleyball players. Exclusion criteria included any history of neuro cognitive deficit or illness, recent concussive injury, and/or substance abuse. The research took place at two universities in Gauteng, South Africa.


Mild traumatic brain injury (MTBI) is a common occurrence with contact sports (Lovell, 2009). In sporting circles MTBI is commonly referred to as concussion and is defined as a brief or negligible loss of consciousness (LOC) and memory with neither lasting for more than an hour (Menascu & Tschechmer, 2011). Risk is elevated with contact sports like football (Matser, Kessels, Lezak, Jordan, & Troost, 1999; Reilly, 1997; Tysvaer & Storli, 1989). By contrast, non-contact sports like volleyball have more of a risk for knee, hand and ankle damage (Briner & Kacmar, 1997). Nonetheless, a concussion cannot be ruled out with any physical sporting requiring repetitive rapid body motion determined by momentary demands on the field of play. There is evidence to suggest that concussion in contact sports often goes unrecognised and undiagnosed, which results in players not seeking medical attention (Al- Kashmiri & Delaney, 2006). 

Concussions are common head injuries in football (mostly from head-to-head or head-to-ground impact or head-to-goal-post injury) and are more likely to incur cognitive deficits than heading a ball (Cusimano et al., 2014). This study sought to investigate the effects of Cumulative Mild Head Injury (CMHI) and post-concussive symptoms (PCS) of football players and compare them to a non-contact sport control group (volleyball players). The research questions related to the goal were a) to examine the extent of cognitive impairments among football players and volleyball players’ pre- and post-season, and b) to determine differences in reaction time incurred by CMHI and PCS between football and volleyball players. 

Instrument The athletes completed a demographic questionnaire which required relevant medical information. To check for post concussive symptomology the Rivermead Post-Concussion Symptom Checklist (RPCSC) was used (King, Crawford, Wenden, Moss, & Wade, 1995). On this measure, high test reliability scores of 0.89 and 0.72 have been found (Eyres, Carey, Gilworth, Neumann, & Tennant, 2014). 

The California Computerised Assessment Package (CalCAP: Miller, 2001) is very sensitive to diffuse brain damage, which is incurred through CMHI, it was thus used to measure differences between the contact sports players (football) and the non-contact controls (volleyball). It is a measure of specific cognitive deficits: Simple Reaction Time, Choice Reaction Time, and Sequential Reaction Time. Previous studies reported high internal consistency scores of between 0.77 and 0.96 for scores from the CalCAP (Miller, 1995; Worth, Savage, Baer, Esty, & Navia, 1993). 


Permission to conduct the research was granted by the participating universities and their ethical committees. Football and volleyball control participants had the research and their rights explained to them and were required to sign written consent forms. 

Pre-season testing was conducted in order to get a baseline measure before the start of the season. The testing took place at an appropriate location at the participating universities’ sports centres. Players were assessed individually. 

The participants had to complete the demographic and medical symptom checklist and the PCS checklist. The participants were then assessed on CalCAP. The baseline testing took approximately 45 minutes for each participant, slightly longer than post-season testing as they had to fill in medical information which would either include or exclude 

them from the study. 

Post-season testing participants completed the PCS checklist questionnaire and were then assessed on the CalCAP. The average time between baseline and post season test for both the football and the volleyball controls was eleven months. The same venues and data administration procedures were used both pre- and post-season. Researchers were the same to obviate administration bias. As the demographic and medical questionnaire did not have to be filled in post-season, testing time was shorter at approximately 25 minutes per participant. 

The players provided individual written consent forms for the study. The participants were informed that if they felt uncomfortable or upset during or after the assessment they would be referred to an appropriate counsellor. 

Reaction time findings

At pre-season testing, volleyball control participants had a faster mean (M) simple reaction time in milliseconds [ms] (335.5 ms, SD +68.9)) than the football participants (M = 386.3 ms, SD +101.7) on Simple Reaction Time 1 (though not statistically significant, p = 0.110). At the end of the season, both the football and the volleyball control group did not differ significantly (p = 0.120). Choice Reaction Time results revealed larger (though not statistically significant (p = 0.429) post-season differences between football players and volleyball controls. Football players had slightly slower mean reaction times post-season (M= 445.8 ms, SD #66.5) than pre-season (M = 444.2 ms, SD +41.0). It is postulated that this could be due to the effects of CMHI as a result of on-field incidents. This result is underpinned by the results of Sequential Reaction Time 1 which revealed a small, statistically significant difference between the football playing group (M = 542.7 ms, SD 

76.6) and the control group (M = 486.00 ms, SD +63.1) post-season (p = 0.033). Sequential Reaction Time 2 results revealed that the football players’ pre-season testing indicated a faster mean reaction time (M = 565.7 ms, SD #104.3) than the control group (M= 642.1 ms, SD =121.2), but it was not statistically significant (p = 0.170). At post season testing, the football players’ reaction time improved (M = 553.4 ms, SD +91.6) as did the control group (M = 601.1 ms, SD =92.2). However, there was no significant difference between the groups (p = 0.157). It appears that playing fast-paced sports, which require dexterity and skill, improves reaction times during the season with or without reaction time training. 

Data analysis

The cognitive profiles of the contact sport (football players) and the non-contact sport controls (volleyball players) were analysed using the Mean (M) and Standard Deviation related to measures of 1 and 2, measured in milliseconds (ms), of the abbreviated CalCAP battery. 

Data were also analysed using Fisher’s Exact Test for the within and between group comparison of the summary of PCS between the football and volleyball control participants at pre-season (baseline) test and post-season (end of season) testing, 

Results and discussion

Pre-season (baseline) and post-season testing (end of season) across the reaction time measures are presented first, followed by pre-season (baseline) and post-season (end of season) findings for the post-concussion measure. Figure 1 presents a summary of the findings on the reaction time measure. 

Post-concussion symptoms

The total frequency of the controls’ symptomology on the PCS checklist revealed that only 6% of these respondents, as opposed to over a quarter (26.67%) of the football group, experienced headaches. Headaches were the most commonly reported PCS measure by football players after sustaining CMHI, particularly in the acute phase. About 50% of the football players reported that they ‘sometimes’ experienced problems with attention and concentration, easily got angry and hurt, and often experienced being nervous or anxious. These symptoms are commensurate with PCS in the chronic phase (Meeham & Bachur, 2009) which supports the small but significant finding on CalCAP Sequential RT 1. 

The results on the Fisher Exact Test for ‘worse symptomology revealed that there were no significant differences between the football and control groups (p = 0.62). However, the results for ‘improved symptoms revealed that there was a small, significant difference between the football group and volleyball controls with 1.3% of the football group reporting ‘improved’ symptoms pre-season as compared to 17.6% of the control group (p= 0.002). This significant outcome suggests chronic PCS in these football players. 

Post Figure 1: Pre-test versus post-test mean scores in milliseconds (ms) on the Choice Reaction Time measure on CalCAP for football (soccer) and the volleyball controls 

Conclusion Findings of this study point towards the possibility that football players are vulnerable to sustaining concussion and CMHI during play (Matser et al., 1999; Reilly, 1997; 

Tysvaer & Storli, 1989) as suggested by their depressed reaction time scores and elevated post-concussion scores. The small sample size and purposive sample suggest that the findings cannot be generalised to football players in general. Future studies should be larger and use randomised samples so that more definitive findings can be made. 

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RAF4 is a legislated form for claimants who seek to be compensated for non-pecuniary loss sustained as a result of a motor collision. The completion of this form assists with determining if the claimant qualifies for such loss alleged to have been incurred.


Medico-Legal Reports which are consequential to an assessment provides the judge in a court of law to the outcome evidence of the assessment and the expert will make recommendations from which the judge can make informed decisions regarding third-party compensation matters.

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